Background: E-cigarette designs, materials, and ingredients are continually evolving, with cotton wicks and diverse coil materials emerging as the popular components of atomisers. Another recent development is the use of nicotine salts in e-liquids to replicate the form of nicotine found in cigarette smoke, which may help cigarette smokers to transition to e-cigarettes. However, scientific understanding of the impact of such innovations on e-cigarette aerosol chemistry is limited.Methods: To address these knowledge gaps, we have conducted a comparative study analyzing relevant toxicant emissions from five e-cigarettes varying in wick, atomiser coil, and benzoic acid content and two tobacco cigarettes, quantifying 97 aerosol constituents and 84 smoke compounds, respectively. Our focus was the potential for benzoic acid in e-liquids and cotton wicks to form aerosol toxicants through thermal degradation reactions, and the potential for nickel–iron alloy coils to catalyze degradation of aerosol formers. In addition, we analyzed e-cigarette emissions for 19 flavor compounds, thermal decomposition products, and e-liquid contaminants that the FDA has recently proposed adding to the established list of Harmful and Potentially Harmful Constituents (HPHCs) in tobacco products.Results: Analyses for benzene and phenol showed no evidence of the thermal decomposition of benzoic acid in the e-cigarettes tested. Measurements of cotton decomposition products, such as carbonyls, hydrocarbons, aromatics, and PAHs, further indicated that cotton wicks can be used without thermal degradation in suitable e-cigarette designs. No evidence was found for enhanced thermal decomposition of propylene glycol or glycerol by the nickel–iron coil. Sixteen of the 19 FDA-proposed compounds were not detected in the e-cigarettes. Comparing toxicant emissions from e-cigarettes and tobacco cigarettes showed that levels of the nine WHO TobReg priority cigarette smoke toxicants were more than 99% lower in the aerosols from each of five e-cigarettes as compared with the commercial and reference cigarettes.Conclusions: Despite continuing evolution in design, components and ingredients, e-cigarettes continue to offer significantly lower toxicant exposure alternatives to cigarette smoking. Over the past 15 years, e-cigarettes have emerged into widespread use as credible alternatives to tobacco cigarettes. Vaping may offer a means of increasing adult cessation of combustible tobacco cigarettes, although there is also the risk of enhanced youth transition to combustible tobacco products  and/or propylene glycol  as aerosol formers, plus a number of optional components including water as a viscosity controller; flavors for consumer appeal; and nicotine, the chief addictive agent in tobacco cigarettes and likely reason for how some smokers have switched from combustible cigarettes to e-cigarettes. Many studies have characterized the chemical composition of e-liquids and e-cigarette aerosols with considerable focus on their low-level toxicants. Several comprehensive integrated chemical studies have measured e-cigarette emissions of up to 142 analytes  comprises cellulose  in early e-cigarettes, now can comprise of kanthal, nickel–iron (NiFe), stainless steel or pure metals such as nickel or titanium. Notably, metal catalysis has been suggested to enhance the thermal decomposition of PG and VG  have adverse respiratory effects. At present, however, there are few data on the emissions of these 19 additional HPHCs, and validated analytical methods for their quantification are not widely available.The US FDA has established a list of more than 90 Harmful and Potentially Harmful Compounds (HPHCs) in tobacco products FDA, , and recIt is of considerable interest to compare e-cigarette toxicant emissions with those of combustible cigarettes. Previous comparisons of this kind have largely focused on per-puff measurements, due to the differences in usage patterns between cigarettes and e-cigarettes. As estimates for puffs per day from e-cigarettes  and Vype ePen3 (Nicoventures Trading Ltd.). Vype ePen2 consists of a reusable section containing a 650-mAh rechargeable battery and an actuation button, a disposable flavor cartridge and a mouthpiece cover. It uses a silica rope wick, and an NiCr coil. The device comes with two power settings ; the high-power setting was used in this study.Vype ePen3 has a different design to the ePen product used in an earlier study  Directive 2011/65/EU; and Annex II Amendment (EU) 2015/863 Restriction of the Use of Certain Hazardous Substances in Electrical and Electronic Equipment (RoHS). Conformity was assessed in accordance with the following harmonized EMC standards: Requirements for Household Appliances, Electric Tools and Similar Apparatus, Part 1 Emission (EN55014-1 and CISPR 14-1) and Part 2 Immunity (EN55014-2 and CISPR 14-2); and Product Family Standard for Aftermarket Electronic Equipment in Vehicles (EN 50498). Conformity was also assessed in accordance with the following harmonized RoHS standards: Technical Documentation ; and Determination of Certain Substances (IEC/EN 62321-1). In addition, the device was certified for low-voltage electrical safety within the IECEE CB Scheme: Household and Similar Electrical Appliances—Safety, Part 1 General Requirements (IEC 60355-1).A fully charged ePen3 battery provides ~200 puffs , which matches the liquid capacity of the pod under these testing conditions.Five e-liquids with two variants of tobacco-style flavor (“Blended Tobacco” and “Master Blend”) of different compositions were used in this study . PG, VG,Blended Tobacco (BT) was tested in ePen2 and ePen3, which differ in coil and wick type, and operating power. Due to the differences in e-cigarette wicks between ePen2 and ePen3, the same PG/VG ratio cannot be used in both products. This is because the silica wick of ePen2 had inferior wicking properties toward high viscosity liquids compared to those of the cotton wick in ePen3. Hence the e-liquid water content was higher in the ePen2 e-liquid than in ePen3, to reduce the liquid viscosity to functional levels. Comparison of the aerosol chemistry between these two products therefore reflects the potential effects of three factors: (1) silica vs cotton wicks; (2) differences in PG/VG/water ratios; and (3) differences in coil power, where ePen3 > ePen2.Master Blend (MB) was tested in three ePen3 e-liquids differing only in nicotine and BA content (which was increased by substitution with VG in the formulation): 12 mg/mL nicotine with low levels of BA; 18 mg/mL nicotine with medium levels of BA; and 30 mg/mL nicotine with high levels of BA. Comparison of the aerosol chemistry among these three products therefore reflects the combined influence of increasing nicotine/BA content and ratio, and small changes (~10%) in VG content (from 32.1 to 34.5% in the formulation).Comparison of the aerosol chemistry between ePen3 Blended Tobacco (18 mg/mL nicotine) and ePen3 Master Blend (18 mg/mL nicotine with medium BA) also provides insight into the influence of BA, together with the effect of a small change in VG level and flavor type.Prior to testing, the commercial and reference cigarettes were marked with the standard butt length as specified in E-cigarette samples were puffed in a dedicated e-cigarette room under a conditioned laboratory environment of 22 ± 2°C and 60 ± 5% relative humidity as specified in Cigarette smoke toxicants and e-cigarette emissions were measured by using Labstat standard methods, as described previously  and extracted by using a platform shaker. The extract was analyzed by selective ion monitoring (SIM) GC-MS using a WAX-type capillary column.3PO4 by shaking for 45 min. The extract was then analyzed by HPLC-UV using a C18 column with detection at 210 nm. Owing to a lack of established methods applicable to smoke analysis, not all of the additional HPHCs were evaluated for the comparator cigarettes.Acetic acid was determined in e-cigarette aerosol by using Labstat method TMS-00115A. In brief, e-cigarette aerosol was generated by using a linear smoking machine and emissions were collected on a 44-mm Cambridge filter pad. The pad was extracted with 20 mL of 0.1% HFor all analyses, 50 puffs of ePen3 or ePen2 were used per collection, which is half the puff number used in previous studies  or limit of quantification (<LOQ), we imputed a value of LOD/2 or the midpoint between LOD and LOQ, respectively, as described previously  , independent samples t-tests are used for the statistical comparison.Statistical comparisons are made between test product and blank emission yields on a per puff basis. When comparing between test products, Generalized Linear Models (GLMs) are used with post-hoc Tukey adjustment with an alpha of 0.05.Statistical comparisons are also made on a per milligram of nicotine basis. This was done by taking the average nicotine per puff value of each of the products and divide the constituent measurement per puff by the average mg of nicotine per puff. Comparisons are made between the reference products and test products. These comparisons do not include blanks, as nicotine was not measured in the blanks. When comparing the test products and reference products, GLMs are used with Overall, the aerosols from five e-cigarette variants  and mainThe nicotine per-puff yields from the ePen3 samples were 3–7 times higher as compared with ePen2, depending on the nicotine concentration of the e-liquid. Nicotine per-puff emissions from ePen2 were 81% lower than those from both cigarettes. Due to the different nicotine concentrations of the ePen3 e-liquids, the percentage difference in nicotine emissions between the ePen3 samples and the two cigarettes varied from 38% lower to 22% higher.Aerosol collected matter (ACM) per puff was, on average, 2.4 times higher from the ePen3 aerosol samples than from ePen2. The per-puff ACM yield from ePen2 was 15–20% higher than the cigarette tar yield. In contrast, the per-puff ACM yields from all e-Pen3 variants were 176–196% higher. ePen2 per-nicotine ACM yields were significantly higher than from the ePen3 samples with at least 18 mg/mL nicotine. The cigarette per-nicotine emissions were not significantly different from each other, but were significantly lower than the corresponding ACM emissions from all of the e-cigarettes.The CO emissions from all e-cigarettes were below the detection limit (BDL) and therefore >99% lower than those from either cigarette. The air/method background values for this group of analytes were all BDL.Water emissions per-puff were comparable among all e-cigarette samples. The per-puff water emissions from all five e-cigarettes were consistently 32–39% lower than those from the two cigarettes. Per-nicotine water emissions from the ePen2 sample were significantly higher than from the ePen3 samples due to the lower nicotine emission from ePen2. Per-nicotine water emissions from the two combustible cigarettes were not significantly different from each other, but were significantly lower than from ePen2 and higher than ePen3 30 mg/mL.Air/method background levels of menthol, diethylene glycol, triacetin, ethylene glycol, and glycidol were all BDL. Background levels of PG and VG were detected but too low to quantify , which may reflect ambient contamination from repeated device testing in the e-cigarette laboratory.Emissions of menthol, diethylene glycol, triacetin, and glycidol were BDL for all five e-cigarettes. Ethylene glycol emissions were quantifiable from two e-cigarettes but BDL with the other samples.All e-cigarette aerosols contained considerable quantities of PG and VG. Per-puff emissions of PG were 6 times higher from the ePen3 samples than from ePen2, reflecting both the higher proportion of PG in the ePen3 e-liquids and the 2–3-fold higher per-puff ACM from ePen3 samples as compared with ePen2. Per-nicotine PG emissions from the two combustible cigarettes were not significantly different from each other, but were significantly lower than those from any of the e-cigarettes. ePen2 PG/nicotine was significantly lower than from all ePen3 variants, except for ePen3 30 mg/mL high BA.In comparison to the B&H Skyblue cigarette, per-puff VG emissions from the five e-cigarettes were between 3,500 and 6,750% higher, and PG emissions were between 32,000 and 183,000% higher. VG and PG emissions were also higher from the e-cigarettes than from the 1R6F cigarette, but to a lesser degree: VG emissions were 900–1,800% higher and PG emissions were 1,300–8,000% higher. Per-nicotine VG emissions from the two combustible cigarettes were not significantly different from each other, but were significantly lower than from any of the e-cigarettes tested in this study. ePen2 VG/nicotine was significantly higher than from all ePen3 variants. Per-nicotine VG from the ePen3 products with a nicotine loading below 30 mg/mL were statistically equivalent.Glycidol was not detected in any of the e-cigarette aerosols, but was quantified in B&H Skyblue cigarette smoke but not in 1R6F smoke. The per-puff emissions from the e-cigarettes were at least 95% lower than those from the B&H Skyblue cigarette. The relative emissions of diethylene glycol and ethylene glycol from e-cigarettes and cigarettes could not be calculated because these analytes were not detected in sufficient numbers of samples.Among the 23 PAHs analyzed, 18 were either not detected in the e-cigarette aerosols or detected at extremely low levels not significantly different to the air/method blank, indicating that these compounds are not generated by the five e-cigarettes tested. For example, benzo(b)fluoranthene, benzo(k)fluoranthene, benzo(a)pyrene, perylene, dibenzanthracene and benzo(j)aceanthrylene were BDL for all air/method blanks and e-cigarette samples. Cyclopentapyrene was <LOQ in the air/method blank, but not detected in any of the e-cigarette samples. Benzo(a)anthracene was <LOQ for air/method blank and three e-cigarette samples, and BDL for two of the ePen3 samples. Benzoperylene was also <LOQ for air/method blank and four e-cigarette samples, but BDL for one ePen3 sample. Benzo(c)phenanthrene, acenaphthene and chrysene were <LOQ for all tested samples. 1-methylnaphthalene, 2-methylnaphthalene, fluorene, acenaphthylene, phenanthrene, fluoranthene, and pyrene were quantified in most or all samples, including the air/method blank, but their levels did not differ significantly between the e-cigarette samples and the air/method blank sample.p <0.05); all other e-cigarette aerosols were not significantly different to the air/method blank. Naphthalene was significantly (up to 70%) higher in all five e-cigarette aerosols than in the air/method blank (p < 0.005).The per-puff levels of four PAHs were higher in e-cigarette aerosols than in air/method blanks. Indenopyrene and benzo(e)pyrene were BDL for the air/method blank and almost all e-cigarette samples, but indenopyrene was <LOQ for ePen2 and benzo(e)pyrene was <LOQ for ePen2 and one ePen3 sample. Anthracene emissions from ePen3  were significantly higher than the air/method blank anthracene] to >99.9% [multiple PAHs]). Similarly, per-puff PAH levels were, on average, 98.7% lower in aerosol from e-cigarettes than in smoke from 1R6F (range 94.5–99.9%). Expressed as a ratio to nicotine all of the PAH emissions from the e-cigarettes were substantially lower  than from both combustible cigarettes. Quantifiable per-nicotine PAH emissions had a tendency to decrease across the e-cigarettes as nicotine emissions increased , but differences between ePen2 and ePen3 were not always significant.None of the volatile organic toxicants examined were detected in the air/method blank or e-cigarette aerosols; all measurements were BDL for the five test products. In contrast, quantifiable levels of all volatile toxicants were detected in smoke from the two tobacco cigarettes. Consequently, the levels of these compounds in the aerosols from the e-cigarettes were, on average, 99.4% lower than those from the B&H Skyblue cigarette on a per-puff basis (range 97–>99.9%), and 99.6% lower than those from 1R6F (range 98.3–>99.9%).Tobacco-specific nitrosamines (TSNAs) emissions both in the air/method sample and all e-cigarette aerosols were BDL. By contrast, all four TSNAs were quantified in the smoke from 1R6F and B&H Skyblue cigarettes. Emissions of TSNAs from all e-cigarette samples were therefore ~99.9% lower than those from the two tobacco cigarettes.n-butyraldehyde, crotonaldehyde, acetoin, and 2,3-pentanedione were BDL for the air/method blank and all e-cigarette samples. These six compounds were quantified in both cigarette smoke samples, and thus their levels were, on average, >99.9% lower in e-cigarette aerosols than in cigarette smoke.Among 18 carbonyls evaluated, emissions of methyl ethyl ketone, 3-buten-2-one, 2,3-Heptanedione was not detected in e-cigarette aerosols, the air/method blank, or the cigarette smoke samples. 2,3-Hexanedione was detected but not quantifiable in the cigarette samples, and not detected in any of the other samples.p = 0.03), but were much higher in the two cigarette smoke samples. In comparison to B&H Skyblue cigarette smoke, levels of formaldehyde were, on average, 97.2% lower in the e-cigarette aerosols (range 94.9–99%). Similarly, the e-cigarettes had, on average, 97% lower formaldehyde emissions as compared with 1R6F (range 94.5–98.9%). Per-nicotine emissions from the two combustible cigarettes were not significantly different from each other, but were significantly higher than from any of the e-cigarettes tested in this study. Per-nicotine formaldehyde emissions from ePen2 were significantly higher than from all ePen3 samples other than the 12 mg/mL low BA sample. All ePen3 variants were not statistically different from each other.Formaldehyde was not quantifiable in the air/method blank, but was quantified in all e-cigarette aerosol samples. Formaldehyde levels per-puff were higher in the ePen2 than in the ePen3 aerosol samples (p < 0.05) in the ePen2 sample than in all ePen3 samples except for ePen3 , where high levels of variance were observed. The cigarette smoke samples contained substantially higher levels of acetaldehyde than any other carbonyl, and the acetaldehyde content of the e-cigarette aerosols was >99.9 lower than the smoke from both combustible cigarettes on both a per-puff and per-nicotine basis.Acetaldehyde was not quantifiable in the air/method blank or two e-cigarette samples , but was quantified in aerosol from ePen2, ePen3  and ePen3 . Both per-puff and per-nicotine levels were significantly higher (p < 0.05), although emissions from the ePen3 BT (18 mg/mL) sample were not significantly different from the air/method blank (p > 0.05). Per-puff emissions from ePen3 BT 18 mg/mLwere lower than from those of the other ePen3 samples (p < 0.05) except for ePen3 (12 mg/mL Low BA). On a per-nicotine basis the e-cigarette acetone emissions were not significantly different to each other, but were significantly lower than those from both combustible cigarettes (which were not significantly different to each other). In comparison to cigarette smoke, acetone emissions from the e-cigarettes were, on average, 99.6–99.8% lower than those from B&H Skyblue and 1R6F cigarette smoke on a per nicotine or per-puff basis, respectively.Acetone was quantified in the air/blank samples and in all e-cigarette aerosols. Acetone emissions were higher in the e-cigarettes than the air/method blank for ePen2 and most ePen3 samples  levels of acrolein than the ePen3 samples (both per-puff and per-nicotine). B&H Skyblue acrolein emissions were significantly higher than from 1R6F; both cigarette smoke emissions were significantly higher than from the e-cigarettes. Acrolein per-puff emissions were 98.2% lower (88% on a per-nicotine basis) from ePen2 than from cigarette smoke; on average, ePen3 samples were >99.9% lower from than from cigarette smoke.Isobutyraldehyde was detected but not quantified in the air/method blank. Regarding the e-cigarettes, it was not detected in two ePen3 samples, but was quantified in the emissions of the other two ePen3 samples and ePen2. Isobutyraldehyde levels per-puff were significantly higher in emissions from ePen3  than in those from ePen2 , which were in turn significantly higher than those from the other ePen3 samples. Per nicotine emissions from ePen2 and ePen3 18 mg BT were significantly higher than from the other e-cigarettes. Per nicotine emissions from B&H were significantly higher than from 1R6F. In comparison to cigarette smoke, e-Pen2 isobutyraldehyde emissions were an average of 97% lower per-puff and 84% lower per-nicotine, and ePen3 emissions were 91–99.9% lower per-puff and 87–99.9% lower per-nicotine.p > 0.05). E-cigarette emissions of glycolaldehyde were, on average, 99.5% lower as compared with cigarette smoke.Glycolaldehyde was not detected in the air/method blank, but was detected in most of the e-cigarette aerosol samples. Levels were generally higher from ePen2 than from the ePen3 samples. Glycolaldehyde was not detected in one ePen3 sample and <LOQ in another; the other two ePen3 samples had quantifiable levels that were not significantly lower than those of the ePen2 sample (p > 0.05). Methyl glyoxal emissions from ePen3  were higher than those from the ePen3  sample, but not statistically significant (p > 0.05). However, methylglyoxal emissions did not differ significantly between ePen2 and ePen3 . Relative to cigarette smoke, glyoxal levels from e-cigarettes were, on average, 96.1% lower than those from B&H Skyblue (range 92.8–99.1%) and 97.3% lower than those from 1R6F (range 95–99.4%). Methylglyoxal levels were, on average, 94.9% lower from e-cigarettes than from either tobacco cigarette (range 92.1–98.0%).Glyoxal and methylglyoxal were not detected in the air/method blank, but were detected at quantifiable levels in all e-cigarette aerosol samples except for ePen3  aerosol, where glyoxal was detected but not quantifiable. Quantifiable glyoxal emissions from the e-cigarettes were not significantly different to each other. Methyl glyoxal emissions were higher  from ePen3  than from ePen2, ePen3 , or ePen3  samples  was not detected in the air/method blank or in any sample other than the ePen2 aerosol, where it was not quantifiable. Diacetyl emissions from the e-cigarettes were, on average, >99.9% lower than those from the two cigarettes.None of the seven phenols measured were detected in the air/method blank, or in any of the e-cigarette aerosol samples . By contrast, phenols were quantified in both cigarette smoke samples. Consequently, levels of the phenols in the e-cigarette aerosols were, on average, 99.8% lower than those in cigarette smoke (range 99.5–>99.9%).Among the 10 flavourants tested, methyl acetate, 1-butanol, isobutyl acetate, furfural, isoamyl acetate, benzyl acetate, ethyl acetoacetate, and acetic acid were not detected in any of the e-cigarette aerosols or the air/method blank . Ethyl acetate was detected, but not quantified in the air/method blank and all e-cigarette aerosol samples. Propionic acid was not detected in the air/method blank or in most of the e-cigarette samples; however, it was detected at sub-quantifiable levels in the ePen3  aerosol and at quantifiable and substantially higher levels in the ePen2 aerosol.Metals emissions from the e-cigarettes were measured after the cartridges containing e-liquids were stored at 40°C/75%RH for 3 months, in an accelerated aging test. The data from this exercise are presented in Of particular interest are the e-cigarette emissions of Ni and Fe, as they constitute the major components of the coil. The data in Of the other metals examined, with aluminum and molybdenum the e-cigarette emissions were not significantly different to the air/method blank values; cigarette smoke emissions were not measured for these metals. Arsenic, copper and mercury cigarette smoke emissions were quantifiable, whereas all e-cigarette emissions were <LOQ or <LOD. Manganese emissions from the e-cigarettes were also <LOQ or <LOD but the cigarette smoke emissions were not measured. Chromium e-cigarette emissions were not significantly different to the air/method blank, which was higher than the cigarette smoke emission level. Cadmium cigarette smoke emissions were 10 ng/puff, but all e-cigarette emissions were <LOD. Lead emissions from two e-cigarettes were quantifiable, but not significantly different to the air/method blank values; cigarette smoke emissions were 25 times higher. Zinc emissions from the 30 mg/mL nicotine high BA sample were significantly higher than from the other e-cigarettes which were not significantly different to the air/method blank level or <LOQ; cigarette smoke emissions were four times higher than from the high BA e-cigarette emission.In this study, we quantified 97 analyte emissions from five e-cigarettes, and 84 analyte emissions from two tobacco cigarettes. Some of these analytes, including many of the additional HPHCs recently proposed by the FDA, have not previously been quantified in e-cigarette aerosols to our knowledge.Recent studies have demonstrated the importance of recording baseline measurements to check for contamination when quantifying low-level emissions from e-cigarettes , which would halve the levels of contaminants per collection, but it is also the result of ongoing improvements in methodology and control of experimental protocols by the measurement laboratory. Progress in these areas does not remove the need for air/method background measurements, as demonstrated in particular by several of the individual PAH measurements. Our previous recommendation to conduct background measurements alongside e-cigarette measurements remains as pertinent today as in earlier investigations  or smaller volatile hydrocarbons. Significant differences in some carbonyl emissions were observed between ePen3  and ePen3 ; however, these differences were not found to respond in a dose-dependent manner to differences in BA content of the three protonated ePen3 samples. We therefore conclude that the presence of BA did not influence carbonyl emissions in this study. Taken as a whole, these data demonstrate the thermal stability of BA in a closed system e-cigarette, consistent with findings from a previous study  show increased transfer to the aerosol. The one metal showing an increased presence in the e-cigarette aerosols, zinc, is quoted as having a boiling point of 249°C in its dibenzoate form CHEMSRC, . TherefoSources of metals in e-cigarettes vapor and their potential health consequences were discussed by Williams et al. . The preDifferences in aerosol chemistry between ePen3  and ePen2  provide a comparative examination of the contribution to toxicant emissions of, respectively, a cotton wick/NiFe coil e-cigarette design and a silica wick/NiCr coil design, although the comparisons are confounded to a degree by differences in the e-liquid composition . As discussed in the introduction, cotton is hypothesized to be more thermally unstable than silica, resulting in higher emissions of carbonyls, acids and esters from low-temperature decomposition reactions (>180°C); higher levels of benzene, toluene, naphthalene (plus derivatives) and anthracene from mid-temperature reactions (>350°C); and greater PAH emissions from higher-temperature reactions (>400–500°C).Comparison of potential low-temperature decomposition products between ePen3 BT and ePen2 BT did not support the hypothesis that emissions are higher in an e-cigarette with a cotton wick. Only isobutyraldehyde was significantly higher in emissions from the cotton wick/NiFe coil product. In contrast, formaldehyde, acetaldehyde, propionaldehyde, and acrolein were significantly higher in the aerosol from the silica wick/NiCr coil product, while the other carbonyls did not differ significantly between the two types of e-cigarette. The levels of acrolein, acetaldehyde, crotonaldehyde, formaldehyde, and propionaldehyde reported here for ePen3 are among the lowest reported in the literature, further supporting the use of cotton wick/NiFe coil as e-cigarette components that minimize toxicant yields . Full toxicity was achieved with 120 puffs from the open-tank device whereas a full cytotoxic curve was not achieved for ePen3 using 1,000 puffs, further supporting the use of cotton wick/NiFe coil technology.The 19 additional compounds that the FDA has proposed adding to established lists of HPHCs in tobacco comprise a number of flavor compounds, aerosol formers, thermal decomposition products and contaminants in e-liquid components FDA, .Among the flavor compounds, propionic acid  was quantifiable in the emissions from ePen2 BT at 155 ng/puff, detected but not quantified in ePen3 BT, and not observed in the other three e-cigarette aerosols. The source of this compound is unclear because propionic acid is not a component of the Blended Tobacco flavor; however, its presence in the aerosol of both of the Blended Tobacco but none of the Master Blend e-cigarettes suggests that it is a flavor-related source. Only one other study has assessed propionic acid emissions from an e-cigarette, reporting values of 1.95–9.01 ng/puff (depending on puffing flowrate) from a refillable tank style e-cigarette  was detected in the air/method blank and each of the e-cigarette aerosols at levels <LOQ. Thus, the presence of this compound seems to arise from contamination sources. To our knowledge, no other studies have reported ethyl acetate emissions from e-cigarettes, although one study identified (but did not quantify) ethyl acetate in aerosol samples  were not detected in any of the e-cigarette aerosols or the air/method blanks. Similarly, none of the other flavourants  and flavor compounds  were detected in any of the samples. Diacetyl  was not detected in the four ePen3 samples, but was detected at <LOQ (<5.8 ng/puff) in the ePen2 sample. It is not a component of e-liquids, so the reason for its presence in the ePen2 aerosol is unclear. Levels of acetoin, acetyl propionyl and diacetyl in the e-cigarette aerosols were reduced by >99.9% as compared with the cigarette smoke of both cigarettes. The complex chemistry of these three compounds in e-liquids has recently been investigated : ePen2 18BT (40) < ePen3 12 low BA (131) < ePen3 18 BT (149) < ePen3 18 Medium BA (168) < 1R6F (210) = B&H Skyblue (210) < ePen3 MB 30 high BA (256). Therefore, nicotine emissions varied more than 6-fold amongst this sample set, with a mean value (166) very close to that of ePen3 18 Medium BA (168). Hence, relative to this mid-point product, calculating toxicant emission values per nicotine raised the values from epen2 product and both the ePen3 12 mg low BA and 18 mg (no BA) nicotine products, while reducing the values from the highest nicotine content ePen3 product and the two cigarettes. The impact of this calculational approach was most significant with the ePen2 product. Consequently, with the quantifiable toxicant/nicotine emissions reported in In contrast, comparing the toxicant/nicotine values in In the present study, we quantified the relative difference in toxicants between e-cigarette emissions and cigarette smoke by calculating percentage reductions. Such calculations are challenged by the fact that many e-cigarette emissions are too low to quantify. A number of approaches have been adopted to impute non-quantifiable values in different datasets, including the midpoint approach used in the present study  per nicotine are  compared to  per puff; with ePen3 BT 18 per nicotine , per puff ; with ePen3 MB 12 Low BA per nicotine  and per puff ; with ePen3 MB 18 Medium BA per nicotine  and per puff ; with ePen3 MB 30 High BA per nicotine  and per puff . The very similar values arise because most of the TobReg9 analytes are either <LOD or <LOQ with the e-cigarettes, and therefore so low in comparison to cigarette smoke values that they show little sensitivity to normalization by puff or by nicotine.The experimental design for comparison of emissions between products with differing wick designs was not ideal through practical necessity. Due to significantly differing wicking/viscosity properties the same e-liquid composition could not be used with the two materials. We matched compositions as closely as possible and used e-liquids that would typically be encountered with commercial examples of both wicking systems, but nevertheless comparisons of aerosol emissions were not straightforward. There were also device design and power setting differences between the products used. However, the aerosols from these devices showed an absence of marker compounds for thermal degradation of cotton, metal-catalyzed PG/VG degradation, or acid mediated coil corrosion. Moreover, despite the higher power and aerosol/puff of the cotton wicked device emissions per puff were not elevated in comparison to the silica wicked product. These findings clearly demonstrate that e-cigarette designs can be developed with cotton wicks, NiFe coils and nicotine benzoate without compromising the low levels of toxicant emissions that can be achieved with e-cigarettes.Although the toxicant emissions from the e-cigarettes showed substantial reductions in comparison to combustible tobacco cigarettes, a study focusing on aerosol chemistry cannot fully investigate the health risks associated with e-cigarette use. Consideration also needs to be given to potential health effects of long-term exposure to the major aerosol components  despite concerns of acid-mediated coil corrosion. Comparison to cigarette smoke emissions demonstrated that e-cigarettes containing these recent design features can offer 99% reductions in priority smoke toxicants. Finally, the absence of any of the FDA proposed 19 additional HPHCs  from these e-cigarettes suggest that the presence of these compounds in e-cigarette aerosols will be largely dictated by manufacturers ingredient choices.The original contributions presented in the study are included in the article/supplementary materials, further inquiries can be directed to the corresponding author/s.AC managed the analytical chemistry program and co-authored the article. KM wrote the manuscript. JT conducted the data analysis. HD directed the study and was responsible for product integrity. All authors contributed to the article and approved the submitted version.British American Tobacco (BAT) was the funding organization for the study. During the course of the study and preparation of the manuscript BAT paid McAdam Scientific Ltd. for the consultancy services of KM, who is also the owner of McAdam Scientific Ltd.; the remaining authors were paid employees of BAT.


To the above, a solution of 10 mL MJE (10 mg) in 50 mL of zinc sulfate was added. Box–Behnken design (Design-Expert software 12.0.1.0) was used for the optimization of ZnO-MJE-NP formulations. The ZnO-MJE-NPs were evaluated for their physicochemical characterization, in vitro release activity, ex vivo permeation across rat skin, antimicrobial activity using sterilized agar media, and antioxidant activity by the DPPH free radical method. The optimized ZnO-MJE-NP formulation (F13) showed a particle size of 257.1 ± 0.76 nm, PDI value of 0.289 ± 0.003, and entrapment efficiency of 79 ± 0.33%. Drug release kinetic models showed that the formulation followed the Korsmeyer–Peppas model with a drug release of 34.50 ± 2.56 at pH 7.4 in 24 h. In ex vivo studies ZnO-MJE-NPs-opt permeation was 63.26%. The antibacterial activity was found to be enhanced in ZnO-MJE-NPs-opt and antioxidant activity was found to be highest (93.14 ± 4.05%) at 100 µg/mL concentrations. The ZnO-MJE-NPs-opt formulation showed prolonged release of the MJE and intensified permeation. Moreover, the formulation was found to show significantly (p < 0.05) better antimicrobial and antioxidant activity as compared to conventional suspension formulations.The objective of the current research is to develop ZnO-Manjistha extract (ZnO-MJE) nanoparticles (NPs) and to investigate their transdermal delivery as well as antimicrobial and antioxidant activity. The optimized formulation was further evaluated based on different parameters. The ZnO-MJE-NPs were prepared by mixing 10 mM ZnSO Rubia cordifolia  and silver nanoparticles (Ag-NPs) with antibacterial activity [Calotropis procera [Poncirus trifoliata [Artemisia annua [A nanocarrier delivery system has been adopted to overcome the disadvantages of repeated dosage administration . Nanotecactivity ,20. Prev procera , Ponciruifoliata , and Artia annua .The formulation development process uses optimization with the approach of quality by design (QbD) to understand the better variable effects and robust quality of the product to confirm the target quality product profile. Design of experiment (DoE) requires critical parameters with fixed ranges to obtain design space (DS) based on the risk assessment process and formulation variables ,25,26,27In the surface response methodology, the Box–Behnken design (BBD) includes powerful, effective, and systematic tools that lessen the time required for the development of pharmaceutical dosage forms with enhanced research output. BBD permits the designer to utilize three levels of each factor to properly achieve the quantification.4·7H2O (% w/v), stirring speed (rpm), and ultrasonic time (minutes). Thereafter, the optimized formulation was analyzed for morphology, particle size, zeta potential, in vitro drug release, ex vivo skin study, stability study, and antimicrobial as well as anti-oxidant activities. The objective of the association of ex vivo study with antimicrobial and anti-oxidant activity was to enhance the therapeutic effect by increasing the drug release to reach systemic circulation quickly.This current study focuses on the development of the formulation of ZnO-NPs of Manjistha extract. Optimization of the formulation was performed by Design-Expert software considering variable parameters such as particle size, % entrapment efficiency, and polydispersity index (PDI), and the independent variables were the concentration of ZnSO4·7H2O) and sodium hydroxide (NaOH) were of analytical grade and were procured from SD Fine Chemical .Manjistha extract was procured from the Sunpure Research Incubation Center, Sunpure Extracts Pvt. Ltd. Delhi, India. The chemicals zinc sulfate (ZnSO4·7H2O) and sodium hydroxide (NaOH) was prepared with a strength of 10 mM  as shown in the The preparation of ZnO-NPs of an aqueous MJE was reported previously . A solut4·7H2O (% w/v), stirring speed (rpm), and ultrasonic time (minutes) were selected as the independent variables, and particle size, PDI, and entrapment efficiency were selected as dependent variables. The software found 13 formulations as expressed in The ZnO-MJE-NPs were optimized using Box–Behnken design (Design-Expert software version 12.0.1.0). Depending upon the preliminary study, the concentration of ZnSO2 value 0.9954 at 285 nm. The limit of detection (LOD) and limit of quantification (LOQ) values were 1.7 and 5 µg/mL, respectively [A standard stock solution of MJE was prepared by accurately dissolving 10 mg of MJE in 10 mL of phosphate buffer at pH 7.4. The calibration curve of MJE was plotted within the concentration range of 5–60 µg/mL, with a linearity equation of Y = 0.0147x − 0.0272, and its Rectively .The Zetasizer-1000 HS  was used to study particle size and PDI. The particle size and PDI were measured with dynamic light scattering (DLS). Water was used to dilute the sample and then placed in a quartz cuvette and analyzed at a 90° scattering angle. All of the batches were analyzed in triplicate, then mean and standard deviation (SD) value was calculated ,32.Zeta potential is an important parameter to predict the stability of the particulate formulation. The electric charge is reflected on the particle surface, which indicates the physical stability of the nanoparticle. It was measured by the Zetasizer-1000 HS  .Transmission Electron Microscopy  was employed to study the shape of the developed nanoparticle. The sample was taken in the carbon-coated grid and stained with phosphotungstic acid under the microscope at 10–100 k times enlargements at 200 kV voltage .The ultracentrifugation method was employed to determine the entrapment efficiency of MJE in the ZnO-MJE-NPs. The ZnO-MJE-NPs were centrifuged at 18,000 rpm and 4 °C for 15 min. The supernatants were collected and free MJE concentration was analyzed at 285 nm by a UV-spectrophotometer . The below mathematical formula was used to calculate the % entrapment efficiency .(1)% EnIn vitro release of the ZnO-MJE-NPs and MJE dispersion was performed at pH 7.4 using a dialysis membrane (molecular weight cut-off 10–12 KDa). Three milliliters of ZnO-MJE-NPs and MJE dispersion (15 mg of MJE) was filled into a dialysis bag and placed in 100 mL dissolution media of different pH. The dissolution medium was stirred regularly at 100 rpm and the temperature was maintained at 37 °C on a magnetic stirrer. The drug content was measured by UV-spectrophotometer. A total of 2 mL of aliquots of the above solution was taken at a different time intervals  and was replaced with the same amount of dissolution medium to maintain the constant volume and concentration gradient ,37. The A Franz diffusion apparatus (9 mm orifice diameter and receptor volume 5 mL) was used to conduct the ex vivo permeation study using rat skin . The stratum corneum with dermal layer in the downwards direction was placed in between the two compartments, i.e., donor and receptor. Tyrode solution pH 7.4 was used as the permeation medium and filled into the receptor compartments . A totalS. Aureus, and E. Coli) using the pour plate method. The study was performed in the sterilized agar medium. The test samples were dispersed in sterilized water [The antimicrobial activity of the prepared ZnO-MJE-NPs was evaluated against the tested organisms (ed water . The preThe percentage of antioxidant activity (% AA) of ZnO-MJE-NPs and MJE dispersion was assessed by 2, 2-Diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging method as described by Brand-Williams et al. . The 0.0A stability study was performed to assess the change in formulation during storage or shelf life. The optimized ZnO-MJE-NP formulation was sealed in glass vials and placed into a stability chamber at 25 ± 1 °C/60% RH for 3 months. Samples were taken at 0, 1, 2, and 3 months and were evaluated for their physical appearance, particle size, and entrapment efficiency .t test was used to assess statistical significance at p ≤ 0.005 for all the parameters. A statistical significance at p < 0.001 was used to assess antimicrobial activity.All the data were expressed in mean ± SD. The Graph Pad prism software was used for statistical analysis. Student’s The polynomial equation for particle size is given below.p < 0.05. The model F-value of 23.30 (p < 0.05) indicated that the model was significant. The quadratic model was evaluated based on an ANOVA and indicated that it was significantly fitted  indicated an adequate signal. The ZnSO4 showed the positive effect on particle size. An increase in the concentration of ZnSO4 resulted in increased particle size because of an increase in the viscosity of the dispersion. The sonication time (B) exhibited a negative effect on particle size. The size of the nanoparticle decreased with increasing sonication time because of the breaking of particles. The stirring speed (C) exhibited a negative effect on the particle size, which meant that with increased stirring speed the particle size decreased from the breaking of the particle, but this was not affected significantly. Graphs of the 3D, contour, and actual and predicted values of the particle size are shown in The results of independent variables on the particle sizes of different formulations are given in y fitted . The F-v2 of 0.9692 was greater than other models , indicating that model was well fitted. The adequate precession of 10.74 (>4) revealed that model was significantly fitted. An ANOVA of the quadratic model was calculated and is given in The effects of independent variables on the PDI of different formulations is given in p < 0.0500) implied the model was significant. The F-value of 0.31 implied that the lack of fit was not significant relative to the pure error. Non-significant lack of fit was desired; we wanted the model to fit  showed a negative effect, and B2 had a positive effect on entrapment efficiency. The effect of independent variables on the entrapment efficiency is graphically expressed in the 3-D and contour plot in 4·7H2O, entrapment efficiency increased, whereas when increasing the ultra-sonication time and stirring speed, the entrapment efficiency decreased because leaching of the drug takes place during the breaking of particles.The equation showed in this case that AB, AC, BC, B², and C² are significant model terms. It indicated that Factor A had a positive effect, and B and C had a negative effect on entrapment efficiency. Interaction terms  showed a positive effect, and AC had a negative effect on entrapment efficiency. However, higher-order terms  was calculated and is shown in 2 value indicated the Korsmeyer–Peppas model was considered as a best-fit model. The value of “n” was found to be 0.273 (pH 7.4), which indicated that drug release from the optimized formulation followed quasi-Fickian diffusion, i.e., non-swellable matrix diffusion [iffusion .−1 and 5.497 × 10−2, respectively. The ER of ZnO-MJE-NPs-opt was 3.60-fold higher than the MJE dispersion. Thus, it can be assumed that the MJE nanoparticles helped to increase the permeation across the skin, and hence, a better therapeutic response can be expected as compared to the MJE dispersion [The permeation study of the ZnO-MJE-NPs-opt and MJE dispersion was done on rat skin for 6 h and data are shown in spersion .S. Aureus and E. Coli. The ZOI values of ZnO-MJE-NPs were found to be 14 ± 2 and 18 ± 1 mm against S. Aureus and E. Coli, respectively, at 24 h. The pure MJE showed a ZOI of 9 ± 1 mm against S. Aureus and 12 ± 2 mm against E. Coli at 24 h. The significantly (p < 0.05) high efficacy of ZnO-MJE-NPs was due to the higher solubility, nanosize, as well as penetration in cells of the microorganism than pure MJE. The difference in the activity was due to the permeability barrier provided by the presence of the cell wall [The antimicrobial activity of ZnO-MJE-NPs and MJE was evaluated on ell wall ,45. The p < 0.05) higher antioxidant activity was found in the optimized ZnO-MJE-NPs than in the pure MJE dispersion. The antioxidant activity of ZnO-MJE-NPs was shown to be highest (93.14 ± 4.05%) at 100 µg/mL concentrations; however, the MJE dispersion showed 60.31 ± 6.05% at 100 µg/mL. The significantly (p < 0.05) high activity of MJE in ZnO-MJE-NPs was due to the high solubility of MJE. MJE has antioxidant and robust scavengers of free radicals [The antioxidant activity of the prepared ZnO-MJE-NPs was evaluated and compared with the MJE extract, and data are shown in radicals . The antStability of nanoformulation is an important requirement for the shelf life of the formulation. The parameters of the stability study of MJE nanoparticles are given in Rubia cordifolia. In this study, the preparation method for the nanoparticles was modified, which helped in achieving a better drug release. A new approach to optimization of the formulation method using BBD lessened the laboratory work with an efficient result. A study carried out for the type of response surface using Box–Behnken design, where a quadratic model was followed, indicated that the result of the optimization of the formulation was good when compared to previous studies. The stability studies of the formulation explained the shelf life of the drug. In vitro and ex vivo comparative drug release studies in the present research indicated that the therapeutic effects of transdermal delivery are good. The nanosize of the particles enhanced their permeability and solubility, which increased the therapeutic effects. This was confirmed by the antimicrobial and anti-oxidant activity.Green synthesis of ZnO-NPs and Ag-NPs has previously been reported for The overall result of this research will be helpful for further research based on different dosage forms as well as pharmacological activities.It was concluded that the Design-Expert software assisted in the development and optimization of the ZnO nanoparticles MJE formulation. The in vitro release results showed that the ZnO nanoparticle formulation has a better release profile. The optimized formulation’s skin permeation and stability study results indicated that this nanoformulation has better therapeutic effects. The ZnO nanoparticles showed better in vitro release, antimicrobial and antioxidant activities, and this optimized formulation may have high therapeutic value.


In this paper, we propose the first analytical procedure—using a screen-printed carbon electrode modified with carbon nanofibers (SPCE/CNFs)—for the detection and quantitative determination of an electroactive disubstituted fused triazinone, namely 4-Cl-PIMT, which is a promising anticancer drug candidate. The electrochemical performances of the sensor were investigated by cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and square-wave adsorptive stripping voltammetry (SWAdSV). The presence of carbon nanofibers on the sensor surface caused a decrease in charge-transfer resistance and an increase in the active surface compared to the bare SPCE. Under the optimised experimental conditions, the proposed voltammetric procedure possesses a good linear response for the determination of 4-Cl-PIMT in the two linear ranges of 0.5–10 nM and 10–100 nM. The low limits of detection and quantification were calculated at 0.099 and 0.33 nM, respectively. In addition, the sensor displays high reproducibility and repeatability, as well as good selectivity. The selectivity was improved through the use of a flow system and a short accumulation time. The SWAdSV procedure with SPCE/CNFs was applied to determine 4-Cl-PIMT in human serum samples. The SWAdSV results were compared to those obtained by the ultra-high-performance liquid chromatography coupled with electrospray ionization/single-quadrupole mass spectrometry (UHPLC-ESI-MS) method. However, these techniques are time-consuming, labour-intensive, and generate a high consumption of reagents. In addition, they require expensive equipment, and due to their complexity, highly qualified analysts are required ,6. In coA whole range of working electrodes is used in voltammetry, e.g., mercury electrodes, glassy carbon electrodes, carbon paste electrodes, or boron-doped diamond electrodes . Since tOften, both conventional and screen-printed electrodes require surface modification for improved selectivity and sensitivity in determining the analyte. The modifier applied to the electrode increases its active surface and improves electron transfer. Among the currently popular modifiers, various types of nanoparticles and nanomaterials are used, including carbon nanomaterials ,20. NanoDespite the above-mentioned facts, no analytical procedure has been described in the literature to date for the quantitative determination of an anticancer fused triazinone (4-Cl-PIMT). On the other hand, this promising small molecule is the subject of our current electrochemical studies due to the attendance (in its structure) of an electroactive azomethine moiety of the ketimine-type, which may be the most susceptible to electrochemical reduction under experimental conditions. The purpose of the present study is to develop and optimise the first analytical procedure—using the most suitable screen-printed sensor coupled with a flow system—which would enable the detection and subsequent quantitative determination of this potential anticancer drug in both solution and enriched serum samples.In the initial stage of the experiments, we compared the voltammetric response of the title compound at the commercially available unmodified screen-printed carbon electrode (SPCE), screen-printed carbon electrode modified with carbon nanofibers (SPCE/CNFs), and screen-printed carbon electrode modified with multiwalled carbon nanotubes (SPCE/MWCNTs). SWV curves of 0.05 and 0.1 µM 4-Cl-PIMT were recorded at all electrodes after 45 s of solution stirring . The ana3[Fe(CN)6]. The obtained curves (ct) compared to the bare SPCE (blue curve) (63.5 vs. 197.3 Ω cm2). Moreover, a better electrochemical performance of the SPCE/CNFs compared to the SPCE is observed as a result of the increase in its active surface due to modification (0.0809 ± 0.0014 vs. 0.061 ± 0.00058 cm2 (n = 3), respectively) + ion peak at m/z 325.1 (retention time: ~6.78 min)Volumes of 0.1% (w/v) TCA solution  in order to precipitate proteins, centrifuged at 4000× g for 10 min, and filtered through a 0.22 µm Millipore filter. The supernatant was analysed in triplicate by the optimised voltammetric procedure and UHPLC-ESI-MS method.Normal human serum purchased from Merck  was tested. Frozen human serum was thawed at room temperature. Then, 100 μL of the human serum sample was 100 times diluted in deionised water spiked with appropriate concentrations of the analyte, transferred to a centrifugal tube, mixed with 50 µL of 7.5%  was proposed as the sensor in the first analytical procedure allowing for the selective and sensitive determination of the most promising anticancer drug candidate from a class of disubstituted fused triazinones, i.e., 4-Cl-PIMT. The increase in the analytical signal of the 4-Cl-PIMT at the SPCE/CNFs compared to an unmodified SPCE results from an increase in the active surface of the working electrode and a reduction in the charge-transfer resistance. The developed SWAdSV procedure is characterised by good sensitivity and selectivity. The calculated LOD and LOQ values were found to be 0.099 and 0.33 nM, respectively. The developed procedure using SPCE/CNFs was successfully used to determine the title analyte in human serum samples. The flow system minimised the effect of human serum matrix on the analyte signal. The SWAdSV results were compared to those obtained by the UHPLC-ESI-MS method, and the relative error values between the results obtained by both methods proved to be satisfying (2.18% and 9.48%). The 4-Cl-PIMT analytical peak at the SPCE/CNFs as a sensor displayed high reproducibility and repeatability.


Patients with rheumatoid arthritis (RA) are almost twice as likely to develop cardiovascular disease (CVD) as those without. However, traditional CVD risks have been shown to underperform in RA patients; thus, we aimed to identify new surrogate risk factors to better reflect their atherosclerotic burden.A total of 380 RA patients with carotid atherosclerosis data were analyzed in this prospective cohort study. The primary outcome was carotid plaque progression over the 3-year follow-up period. Risk parameters assessed for the progression of carotid plaque were categorized as demographics, traditional CVD risks, RA-related risks, and bone parameters.p = 0.025), serum C-terminal telopeptide of type-I collagen (CTX-I) (p = 0.014), and femur and distal radius bone mass density (BMD) , as well as traditional CVD risk factors. In multivariable analyses, the bone parameters of serum CTX-I and distal radius BMD proved to be independent predictors of the progression of carotid plaque along with hyperlipidemia, smoking, and baseline carotid plaque . Adding both serum CTX-I and distal radius BMD increased the carotid plaque progression prediction model’s percentage of explained variance from 24 to 30%.The progression of carotid plaque was associated with the level of rheumatoid factor (High serum CTX-I and lower radius BMD, reflecting high bone turnover, were independent risk factors for the progression of carotid plaque in RA patients, implicating the direct or indirect role of bone metabolism on the atherosclerotic burden.The online version contains supplementary material available at 10.1186/s13075-021-02642-4. Patients with rheumatoid arthritis (RA) are nearly twice as likely to die before the age of 75 compared with people without the disease. The leading cause of this excess mortality among all age groups is cardiovascular disease (CVD) . This isThe cellular component of atherosclerotic lesions predominately comprises smooth muscle cells and macrophages . MacrophTo investigate the risk factors for CVD and its contribution to mortality in RA patients, we established the Kyungpook National University Hospital (KNUH) Atherosclerosis Risk in RA (KARRA) cohort. In the previous study,  we observed that the presence of carotid plaque in RA patients was associated with a cumulative inflammatory burden, such as the cumulative erythrocyte sedimentation rate (ESR) and health assessment questionnaire (HAQ) score, as well as current disease activity, including the Disease Activity Score-28 using ESR (DAS28-ESR) . HoweverDuring the period from September 2009 to November 2011, 417 consecutive RA patients, who fulfilled the 1987 American College of Rheumatology Classification for RA, were recruited from the rheumatology clinic of KNUH to establish the KARRA cohort for a prospective, longitudinal, observation study . At baseThe primary outcome in this study was the progression of carotid plaque by carotid ultrasound examination after the 3-year follow-up period. Carotid ultrasound examination was conducted using high-resolution B-mode images acquired with LOGIQ7 ultrasound system  with a 10-MHz linear transducer by one qualified ultrasound technician. Carotid plaque was defined as either a focal structure that encroaches into the arterial lumen by at least 50% of the surrounding (intima-media thickness) IMT value or a thickness of > 1.5 mm as measured from the media–adventitia interface to the intima–lumen interface. The progression of carotid plaque was defined as an increase in the number of carotid plaques at the 3-year follow-up ultrasound compared to that at baseline. The carotid IMT was measured using continuous static images, 20-mm in length, obtained from 10-mm below the proximal common carotid artery through the middle of the internal carotid artery . The meaDemographic and clinical parameters of CVD- and RA-associated risk factors were obtained by experienced rheumatologists and clinical research nurses Table . At base2) and T scores, which defines scores between − 1 and − 2.5 as osteopenia and scores below − 2.5 as osteoporosis.Morning venipuncture blood samples were obtained after a 12-h fast and were analyzed in KNUH clinical laboratories. Blood tests for metabolic diseases  and RA ) were checked. Serum osteocalcin and C-terminal telopeptide of type-I collagen (CTX-I) was determined by automated radioimmunoassay and the electro-chemiluminescence method, respectively. BMD was evaluated at the lumbar spine, femoral neck, and distal radius by dual-energy X-ray absorptiometry using a Discovery W densitometer . BMD values were expressed in absolute values (g/cmt test for continuous variables and with the chi-square test for discrete parameters. The odds ratio (OR) for continuous variables was assessed by logistic regression with a single continuous variable.The association with the primary end point of carotid plaque progression was compared using a Student p value < 0.1 in univariate analyses. The first model included only clinical variables as the covariate, such as age, male sex, WHR, hypertension, hypercholesterolemia, smoking status, serum LDL-cholesterol, uric acid level, presence of baseline carotid plaque, mHAQ, RF, and ESR. The second and third model added the bone parameters of serum CTX-1 and distal radius BMD, respectively, and the fourth model included both bone parameters to clinical variables. The goodness of fit of each model was determined with the Nagelkerke R2 coefficient of determination. All statistical analyses were performed with the statistical package software IBM SPSS® for Windows version 25.Multivariable analyses were performed in 4 models by binary logistic regression analysis, with forward selection of the variables that demonstrated a statistical significance of The 3-year follow-up carotid ultrasound performed on these 309 RA patients revealed the development of new plaque in 49 of the 169 patients without baseline carotid plaque, and the progression of plaque in 89 of the 140 patients with baseline plaque. Consequently, a total of 138 patients (44.7%) demonstrated carotid plaque progression, but the other 171 patients did not  and thick carotid IMT (p < 0.001) at baseline. Among the RA-related factors, only the level of rheumatoid factor was associated with the progression of carotid plaque after 3 years (p = 0.025), although the current ESR was marginally associated (p = 0.059). On the other hand, the parameters for disease activity (DAS-28 ESR), disease duration, or medications, including steroid, MTX, or biologics, failed to predict the progression of carotid plaque at the 3-year follow-up (Table p = 0.014), and a lower femur and radius BMD  had a higher incidence of carotid plaque progression  and in those with higher LDL-cholesterol (p = 0.005) and mean carotid IMT at baseline (p < 0.001). There was no significant association between the RA-associated risk factors and the development of new carotid plaque. The patients with an increased level of serum osteocalcin (p = 0.021) and CTX-1 (p = 0.014) at baseline had a higher incidence of carotid plaque development at the 3-year follow-up. In addition, lower baseline femur and radius BMDs were also significant risk factors for the development of carotid plaque at the 3-year follow-up   for carotid plaque progression. Then, we added the bone parameters, CTX-I and distal radius BMD, to clinical models 2 and 3, respectively. The serum CTX-I and distal radius BMD remained as independent risk factor and were the most important predictors of carotid plaque progression among those evaluated; the β coefficient of CTX-1 and radius BMD were 1.539 and -3.057, respectively. These parameters could increase the explained variance of the model (R2) to 27.3% and 25.6%, respectively. Adding both CTX-I and distal radius BMD to the clinical risk factors in model 4 could explain 29.7% of the variance in the regression model for predicting carotid plaque progression  showed only about 30% of the plaque progression incidence as the middle and lower tertile groups of serum CTX-I, and it increased to 37.5% in the upper CTX-I tertile group. In the middle tertile group of radius BMD (0.530–0.625 g/cm2), the incidence of carotid plaque progression was gradually increased by the serum CTX-I level, that is 25.0%, 34.5% and 45.7% in the lower, middle, and upper CTX-I tertile groups, respectively. In the lower tertile group of radius BMD (< 0.530 g/cm2), plaque progression was observed in 42% of the patients in the lower tertile of serum CTX-I, and in nearly 60%–70% of the patient in middle and upper tertiles  signaling . The canContrary to our expectation, the disease activity of RA at baseline assessed by DAS28-ESR did not affect the progression of carotid plaque as well as the mean cIMT Table . The 3-yWe investigated the potential risk for the progression of carotid plaque in RA patient in this prospective, observational study. The bone parameters of lower distal radius BMD and elevated serum CTX-1 level, along with hyperlipidemia, smoking, and the presence of carotid plaque at baseline were independent risk factors for the progression of atherosclerosis in RA patients. Our study sheds light on the connection between bone metabolism and atherosclerosis. Further clinical investigation is needed to determine whether this connection is RA-specific or a common phenomenon in the general population.Additional file 1: Supplementary Figure S1. Forest plot showing the odds ratio for risk of the progression of carotid plaque. Supplementary Figure S2. RA disease activity at baseline and changes in mean carotid IMT. Supplementary Table S1. Disease activity and the progression of carotid plaque in RA patients


Pre-miRNA-377 is a hairpin-shaped regulatory RNA associated with heart failure. Here, we use single-molecule optical tweezers to unzip pre-miRNA-377 and study its stability and dynamics. We show that magnesium ions have a strong stabilizing effect, and that sodium ions stabilize the hairpin more than potassium ions. The hairpin unfolds in a single step, regardless of buffer composition. Interestingly, hairpin folding occurs either in a single step (type 1) or through the formation of intermediates, in multiple steps (type 2) or gradually (type 3). Type 3 occurs only in the presence of both sodium and magnesium, while type 1 and 2 take place in all buffers, with type 1 being the most prevalent. By reducing the size of the native hairpin loop from fourteen to four nucleotides, we demonstrate that the folding heterogeneity originates from the large size of the hairpin loop. Further, while efficient pre-miRNA-377 binders are lacking, we demonstrate that the recently developed C2 ligand displays bimodal activity: it enhances the mechanical stability of the pre-miRNA-377 hairpin and perturbs its folding. The knowledge regarding pre-miRNA stability and dynamics that we provide is important in understanding its regulatory function and how it can be modulated to achieve a therapeutic effect, e.g., in heart failure treatment. Precursor microRNAs (pre-miRNAs) are hairpin-shaped precursors of the short ~22 nt), single-stranded microRNAs miRNAs; A, which 2 nt, sin+ stem cells deficient in miRNA-377 into the mouse ischemic myocardium was shown to promote their regenerative ability through angiogenesis (blood vessel formation) [Recently, miRNA-377 A has emermation) . The uprrmation) ,7. Recenrmation) . Heart frmation) ,9,10. DuDK, of 190 ± 50 nM [DK = 3.0 ± 0.3 μM) compared to C1 (DK = 65 ± 10 μM); hence, it has been selected herein as the small-molecule ligand for the development of the optical tweezer-based pre-miRNA-binding assay  and riblnificus ). Anothelnificus ). Howeve+) or potassium (K+) ions in the presence or absence of magnesium (Mg2+), providing a measure of the pre-miRNA-377′s mechanical stability in various ionic environments. We also investigated the binding interactions between pre-miRNA-377 and C2, which allowed us to pinpoint the impact of the small molecule on the hairpin’s unfolding and folding. With this study, we gained insight into the pre-miRNA-377 structure–dynamics relationship, which will be beneficial for further structure–function investigations as well as small-molecule ligand design in heart failure therapies directed towards the regulation of miRNA-377 levels.Herein, optical tweezers permitted us to investigate how human pre-miRNA-377 unfolds and folds under physiological conditions. Without using high temperatures or denaturing agents, but by applying a force to the ends of a single pre-miRNA-377 molecule, we were able to directly observe its transition from the folded (hairpin) state to the unfolded state and vice versa. Force and molecule end-to-end distance (extension) were measured and compared between different buffers, containing sodium  using UNAFold  showed that it adopts a hairpin structure with four unpaired regions: an A:C mismatch, two A-bulges, and a large hairpin loop , instead of UNAFold. This comparison suggests that while the stem is well-defined, different base-stacking interactions are possible within the pre-miRNA-377 hairpin loop, leading to alternative conformations. Irrespective of the tool selected for the secondary structure analysis, all unpaired regions of the pre-miRNA-377, as well as the cleavage site of the Dicer enzyme , indicating high hairpin stability.Pre-miRNAs are ~70 nt long hairpins consisting of a non-perfect stem and a terminal hairpin loop ,23. Our pin loop A. The laFor the optical tweezers experiments, we designed the WT pre-miRNA-377 to be flanked at each end by a double-stranded DNA (dsDNA) only 29 bp in length see B. To theUF) and 10.1 ± 0.3 pN (FF), respectively (UE = 20.8 ± 0.3 nm) and folding (FE = 21.0 ± 0.5 nm) corresponded to 50 ± 3 nt, confirming that the synthetized construct had the anticipated length.The identity and conformity of our construct was investigated in initial experiments in high-salt buffer . Furthermore, the unfolding force was independent of folding type  and K+/Mg2+ (8.1 ± 0.4 pN) buffers, and at a significantly lower force in the Na+ buffer (7.2 ± 0.4 pN)  . In concF; The force difference between the unfolding and folding transitions ΔF; C was higG, calculated in UNAFold was −22.4 kcal/mole and −22.2 kcal/mole for the WT pre-miRNA-377 and the loop mutant, respectively.To investigate the origin of the complexity of the pre-miRNA-377 conformational dynamics, we designed a loop mutant of the WT pre-miRNA-377. The loop mutant 40 nt; A is iden+/Mg2+ buffer  and typical examples are shown in F (2.0 ± 0.5 pN) was significantly lower than for the WT pre-miRNA-377  and, when unfolded, it inhibits folding (decreases FF and pushes the system completely to type 2 or type 3). The folding inhibition is most likely due to an interaction between the C2 ligand and the unfolded pre-miRNA-377 molecule. Although mechanical enhancement effects have been previously observed in a variety of protein–ligand systems [add adenine riboswitch-adenine [Having characterized the pre-miRNA-377 alone, we investigated the effect of ligand binding on pre-miRNA-377 unfolding and folding. For our experiments, we used the recently developed pre-miRNA-377 ligand: compound 2 , to theMiRNAs are powerful gene regulators, whose features and abundance affect human health. Knowledge regarding the stability and conformational dynamics of their precursors, pre-miRNAs, is important for a better understanding of the miRNA biosynthesis and for designing effective therapies stimulating or inhibiting this process, e.g., to treat cancer as well as neurological, autoimmune, and cardiovascular diseases.DK in the millimolar range [Our optical tweezers study provides the first insight into the stability and conformational dynamics of the human pre-miRNA-377, an important therapeutic target in heart failure. These two features are highly dependent on the ionic strength of the solution as well as the counterions used ,39,40,41ar range . Since iar range , the binBy applying optical tweezers, we were also able to disentangle pre-miRNA-377′s folding pathways. It is worth noting that duplex stem–loop hairpins of model DNAs ,46,47 anInterestingly, the folding heterogeneity and the richness of intermediary structures have not been shown before, neither for the pre-miRNA-377 nor for any other pre-miRNA. Future studies will likely show whether these features are conserved among pre-miRNAs and whether they affect gene expression regulation. Recently, the stimulatory function of programmed ribosomal frameshifting (PRF) structures has been attributed to the heterogeneity of their folding dynamics, discriminating the importance of other features, such as unfolding force and rate or barrier height, for stimulation efficiency . ExampleOur investigation also provides a source of understanding of the observed complexity in pre-miRNA-377 dynamics. Reducing the size of the pre-miRNA-377′s hairpin loop to the minimum, four nucleotides, affects its folding pathways. The loop mutant, despite possessing the two bulges and the internal loop of the WT construct, displays an “all-or-none” behavior in unzipping and zipping. Based on these comparative studies of the WT pre-miRNA-377 and its loop mutant, we demonstrate that the folding heterogeneity of the pre-miRNA-377 originates from its large hairpin loop, which results in the formation of local energy minima structures and therefore prevents rapid exchange between fully the folded and fully unfolded states of the molecule.DK = 65 ± 10 μM vs. 3.0 ± 0.3 μM, respectively [DK of the TGP-377 dimer  structure of the α-synuclein-coding mRNA [Finally, we showed for the first time that the optical tweezers technique is powerful for observing the mechanics of ligand binding to pre-miRNA hairpins. Using the previously identified C2 ligand , we attring mRNA .Apart from increasing the fundamental knowledge of the secondary structure, stability, and dynamics of pre-miRNAs and of the structure–dynamics relationship of RNA hairpins, our study also provides a technical advancement on how to utilize mechanical force ramp and molecular extension to reveal the transient states of pre-miRNAs under physiologically relevant conditions. In addition, for the first time, we demonstrate how to use short dsDNA handles  to studyStudying pre-miRNAs with single-molecule optical tweezers comes with both advantages and disadvantages. Thanks to our single-molecule approach, conformational dynamics could be studied and quantified, allowing us to determine that pre-miRNA-377 forms intermediate structures and that this is due to the large hairpin loop of the molecule. However, further studies are needed to examine the functional consequences of these partially folded structures. In particular, it would be interesting to explore whether they can affect Dicer binding and hence miRNA biosynthesis and/or RNAi-mediated gene expression regulation. Previous studies on other types of regulatory RNAs, such as PRF structures and riboswitches, have shown the role of folding heterogeneity in the regulatory mechanisms of these RNAs ,19,21. TIn summary, single-molecule force spectroscopy has enabled us to gain an insight into the structure, stability, and conformational dynamics of a therapeutically very relevant pre-miRNA, the human pre-miRNA-377, which is associated with heart failure. The study highlights the formation of intermediates upon the folding of the pre-miRNA-377 hairpin. This feature of the pre-miRNA could be very interesting for further studies as it may potentially function as a regulatory mechanism in RNAi, by analogy to the folding heterogeneity of other regulatory RNAs reported so far in the literature ,19,21. HTwo pre-miRNA-377 constructs were studied: WT pre-miRNA-377 A. They wLyophilized oligonucleotides were dissolved in RNase-free water to a final concentration of 100 μM. Next, a digoxigenin-labeled tail of ~50 nt was added to the 3′ end of the oligonucleotide. The 3′ modification was performed at 37 °C using Terminal Transferase kit  and at the digoxigenin-11-dUTP  to dATP  ratio of 1:10. The reaction was stopped after 15 min by adding 0.5 M EDTA, pH 8.0, yielding 5.0 μM oligonucleotide with the 3′ DIG-dUTP tail. The obtained product was purified at room temperature using the RNeasy Mini Kit  with 250 mL of ethanol 99.7% for sample preparation and 30 mL of RNase-free water for elution. The purified tailed oligonucleotide was subsequently diluted in RNase-free water to a concentration of 2.0 μM. A 29 nt single-stranded DNA (ssDNA) oligonucleotide complementary to the 5′ and 3′ ssDNA handles (splint) was added to the purified tailed oligonucleotide at an equimolar ratio. Next, they were hybridized in a splint buffer  to obtain the pre-miRNA-377 construct with dsDNA handles, suitable for the optical tweezers’ measurements. The hybridization was carried out in a PCR machine and comprised the following steps: heating at 90 °C for 1.0 min, cooling from 90–80 °C in 10 s, heating at 80 °C for 10 s, cooling from 80–40 °C at 0.5 °C/10 s and from 40–10 °C at 0.5 °C/20 s. The obtained sample was next diluted in RNase-free water to a concentration of 0.2 μM. All the sample preparation steps were carried out in RNase-free PCR tubes. The final sample was aliquoted and stored at −80 °C until its use in the experiments.−1 cm−1 for the WT pre-miRNA-377 and 955,300 M−1 cm−1 for the loop mutant) was calculated as the sum of molar absorptivities of their 5′ DNA , RNA , and 3′ DNA  fragments. For the DNA fragments, the molar absorptivity was approximated by a linear combination of the molar absorptivities of individual nucleotides at 260 nm  and, since the RNA sequence yields a double-helix hairpin, the calculated value was multiplied by 0.9 to account for the base-stacking interactions within the hairpin.The molar absorptivity of the oligonucleotides at 260 nm  and mul+/Mg2+ buffer  vs. Na+ buffer . Experiments to study the impact of monovalent salt ions (potassium vs. sodium ions) were performed in Na+/Mg2+ buffer vs. K+/Mg2+ buffer .Experiments to validate the synthesis of the sample of interest were performed in high-salt buffer , which yields high resolution in the optical tweezers’ measurements, as a consequence of the high unfolding force required. Experiments to study the impact of divalent metal ions (magnesium ions) were performed in NaD; F) acting on the hairpin, yielding a force–distance curve (FDC)  that recorded the position of the trap. The remaining light was focused through a water-immersion objective lens  to form the trap. Light exiting the trap was collected by an identical objective lens and directed to a PSD and a photodiode to measure the forces on the trapped beads. Data were recorded at a frequency of 1.0 kHz. The microfluidic chamber was mounted between the objectives and moved using a motorized stage. In an optical tweezers experiment, an anti-digoxigenin-coated bead was captured in the optical trap, while a streptavidin-coated bead was immobilized by suction at the tip of the micropipette B. See Suve (FDC) C. An expve (FDC) . Tens tove (FDC) . Data aristogram D. All me+/Mg2+ buffer and at RT.The small-molecule ligand named compound 2 C2; A, being E) at a given force (F) was obtained using the formula [f is the measure of a force jump in an FDC, effk is the effective stiffness of the hairpin in the folded state , and dx is the double helix diameter. The dx was modeled as a single bond of length d = 2.0 nm and the mathematical equation for this model is given by:Bk is the Boltzmann constant and T is the absolute temperature (298 K). Force histograms were obtained by combining force values from different FDCs and plotting their relative frequency for the bin size of 0.5 pN. Extension histograms were obtained in an analogous way (bin size of 0.5 nm). The errors reported for each bin in the histograms were obtained by calculating the error of the relative frequency of forces/extensions in each bin over different bead pairs. The force difference (ΔF) was determined as the median of individual force differences:ith FDC (Folding (relax) events were divided into three different types based on their folding pattern  and analyzed separately within each FDC type. The unfolding and folding forces were observed as sudden jumps in FDCs C and the formula :(1)EF=Δf ith FDC C. The pr


Objective: The study aims to establish an magnetic resonance imaging radiomics signature-based nomogram for predicting the progression-free survival of intermediate and advanced hepatocellular carcinoma (HCC) patients treated with transcatheter arterial chemoembolization (TACE) plus radiofrequency ablationMaterials and Methods: A total of 113 intermediate and advanced HCC patients treated with TACE and RFA were eligible for this study. Patients were classified into a training cohort (n = 78 cases) and a validation cohort (n = 35 cases). Radiomics features were extracted from contrast-enhanced T1W images by analysis kit software. Dimension reduction was conducted to select optimal features using the least absolute shrinkage and selection operator (LASSO). A rad-score was calculated and used to classify the patients into high-risk and low-risk groups and further integrated into multivariate Cox analysis. Two prediction models based on radiomics signature combined with or without clinical factors and a clinical model based on clinical factors were developed. A nomogram comcined radiomics signature and clinical factors were established and the concordance index (C-index) was used for measuring discrimination ability of the model, calibration curve was used for measuring calibration ability, and decision curve and clinical impact curve are used for measuring clinical utility.Results: Eight radiomics features were selected by LASSO, and the cut-off of the Rad-score was 1.62. The C-index of the radiomics signature for PFS was 0.646 (95%: 0.582–0.71) in the training cohort and 0.669 (95% CI:0.572–0.766) in validation cohort. The median PFS of the low-risk group [30.4 (95% CI: 19.41–41.38)] months was higher than that of the high-risk group [8.1 (95% CI: 4.41–11.79)] months in the training cohort  and was verified in the validation cohort. Multivariate Cox analysis showed that BCLC stage , AFP level , time interval  and radiomics signature  were independent prognostic factors of PFS in the training cohort. The C-index of the combined model in the training cohort was higher than that of clinical model for PFS prediction . Similarly, The C-index of the combined model in the validation cohort, was higher than that of clinical model . The calibration curve, decision curve and clinical impact curve showed that the nomogram can be used to accurately predict the PFS of patients.Conclusion: The radiomics signature was a prognostic risk factor, and a nomogram combined radiomics and clinical factors acts as a new strategy for predicted the PFS of intermediate and advanced HCC treated with TACE plus RFA. Primary liver cancer (PLC) is the sixth most common malignant cancer and the fourth leading cause of cancer-related death worldwide . A totalTACE pretreatment reduces or eliminates the “heat sink” caused by blood flow during the RFA procedure and clearly shows lesion contours on CT because of lipiodol deposition. These factors may broaden the extent of coagulation necrosis and ultimately result in better outcomes . In addiEfforts have been made to select appropriate candidates for TACE and RFA treatment based on the Barcelona Clinic Liver Cancer (BCLC) staging system and on histopathologic grade, AFP and performance status as well as vascular invasion . In addiRadiomics is a field that involves tumour segmentation, feature extraction and radiomics model building using the high-throughput mining of quantitative image features extracted from images such as magnetic resonance imaging (MRI) and computed tomography (CT) as well as positron emission computed tomography . RadiomiThis study aimed to develop and verify a novel radiomics model including a radiomics signature and clinical risk factors that can be used to predict the PFS of intermediate and advanced HCC patients treated with a combination of TACE and RFA.n = 86) (II) BCLC stage A or D (n = 73) (III) Child-Pugh class C (22) (IV) lack of available pretreatment MR images 3 months before initial treatment and of follow-up MRI images (n = 58) (V) lost to follow-up (n = 66) (VI) target lesion inadequate for radiomics analysis (n = 34). Finally, 113 patients were analysed in this study.This retrospective study was approved by the institutional ethics committee. A total of 452 HCC patients who received initial TACE plus RFA from January 2010 to December 2018 were initially included. The exclusion scheme is shown in 2). MRI images were exported in DICOM format.All patients were scanned using a 3.0 T MR scanner  before and after TACE plus RFA treatment. Dynamic contrast MRI images were obtained by injecting dimeglumine gadopentetate  at a dose of 0.1 mmol per kilogram body weight. The scanning parameters were as follows: 1) spectral presaturation with inversion recovery T2-weighted sequence , 7 mm slice thickness, 1 mm interslice gap, 200 × 195 matrix size); 2) breath-hold unenhanced and contrast-enhanced mdIXON-T1WI (water) sequence  for four dynamic phases: hepatic arterial phase (15 s), portal venous phase (50 s), substantial period phase (90 s) and delayed phase (180 s); and 3) breath-hold diffusion-weighted echoplanar sequence  was carefully inserted into the blood supply artery of the lesion, and the chemotherapeutic and embolic agents were injected through the microcatheter under DSA. Angiography was performed before the end of embolization to confirm satisfactory embolization of the feeding artery.Percutaneous RFA was described in our previous study W. . BrieflyPFS was the end point of this study. PFS was defined as the time from the date of TACE until the date of relapse (relapse refers to intrahepatic recurrence or extrahepatic metastasis) or until the date on which the patient was last known to be free of relapse. The first outpatient clinic visits were conducted within 4–6 weeks after TACE plus RFA treatments and every 2–3 months thereafter MRI images were obtained and used to track tumour progression. Serum AFP levels, liver function and blood cell levels were also tested.www.itksnap.org). All preoperative contrast-enhanded T1-weighted images were then imported into Artificial Intelligence Kit software  to obtain quantitative VOI information. A total of 396 radiomics features divided into five categories, including histogram, form factors, grey-level co-occurrence matrix (GLCM), grey-level size zone matrix (GLSZM) and run-length matrix (RLM), were extracted.Two experienced radiologists with more than 10 years of experience in clinical HCC diagnosis independently and semi-automatically conducted delineation of the volume of interest (VOI) using ITK-SNAP (Intra- and interclass correlation coefficients (ICCs) were applied to evaluate the intra- and inter-observer agreement of VOI segmentation and radiomics feature extraction. The two readers obtained the radiomics features twice with at least a 1-month interval between the two readings, and the inter-observer agreement and intraclass correlation were computed. An ICC value greater than 0.75 was considered to indicate good agreement.n = 78 cases) and a validation cohort (n = 35 cases) for radiomics model building and verification, respectively. The least absolute shrinkage and selection operator (LASSO) logistic regression algorithm was further conducted for feature selection in the training cohort, and a rad-score was calculated for each patient based on the selected radiomics features in both the training and validation cohorts using Cox-regression. The predictive accuracy of the radiomics signature was evaluated based on the area under the curve (AUC) of the receiver operator characteristic (ROC) curve in the training cohort and verified in the validation cohort. An optimal cut-off value of the rad-score was calculated based on Youden index and used to classify the patients into a high-risk group and a low-risk group for recurrence-free survival analysis. The PFS in the two groups was analysed by the Kaplan-Meier method, and the difference was calculated using the log-rank test.The features were then standardized and normalized by the Z score method, and abnormal values were replaced with the median of the parameter. Before dimension reduction, all patients were randomly divided into a training cohort , calibration curve, decision curve and clinical impact curve.Univariate Cox proportional hazard regression analysis was applied to select the clinical characteristics with p-values < 0.05 were defined as statistically significant.All statistical analyses were performed using SPSS software (SPSS version 22.0) and R software (R version 4.0.3). 2 test and Fisher’s exact test. Student’s t-test was used to determine the significant difference between the training and validation groups for normally distributed data; otherwise, the Mann-Whitney test was used. Feature selection was performed using the LASSO logistic regression model, which was conducted by 10-fold cross-validation. Univariate analysis using Cox’s proportional hazards regression model was applied to select the variables for multivariate analysis. The concordance index (C-index) was used to evaluate the discrimination of the radiomics, clinical and combined prediction models. The agreement between predictions from the model and observed outcomes were measured by calibration curve, assessed by calculating the Hosmer–Lemeshow goodness-of-fit test. The clinical usefulness of the prediction models was estimated based on decision curves and clinical impact curve.Categorical variables are shown as frequencies, and continuous variables are presented as mean and standard deviation or as median and 95% confidence interval (CI) values. Categorical variables were compared using the χA total of 113 patients were eligible for this study; among these, 80 patients (70.79%) had confirmed tumour recurrence according to the clinical final observer outcome. The median PFS was 13.20 months, and the 95% CI was 9.78–16.61. The overall 1-, 2-, and 3-years cumulative PFS rates of the patients were 57.54, 31.34, and 20.37%, respectively. There were no significant differences in sex, age, HBsAg, cirrhosis, BCLC stage, Child-Pugh classification, AFP level, tumour diameter, node number, metastasis, portal vein thrombosis, TACE-RFA procedures and time interval between TACE and RFA treatment in the training and validation cohorts .Satisfactory inter- and intra-observer reproducibility of feature extraction was achieved. The intra-observer ICC calculated based on two measurements ranged from 0.81 to 0.93, and the interobserver agreement between the two readers ranged from 0.79 to 0.90. The extracted features are shown in p < 0.0001, p = 0.0049, He C-index of the radiomics signature for PFS was 0.646(95%: 0.582–0.71) in the training cohort and 0.669(95% CI: 0.572–0.766) in validation cohort. In the training cohort, the median PFS was 30.4 (95% CI: 19.41–41.38) months in the low-risk group, while the median PFS was 8.1 (95% CI: 4.41–11.79) months in the high-risk group. Compared with the high-risk group, the PFS of the low-risk group was significantly longer : 2.52, 95% CI: 1.42–4.47, p = 0.002), AFP level , time interval  and radiomics signature  were independent prognostic factors of PFS , AFP (≥200 ng/ml vs. <200 ng/ml), interval (<14 days vs. ≥14 days) and radiomics signature (high-risk vs. low-risk), had s of PFS .p < 0.001]. similarly, The C-index of the combined model in the validation cohort, was higher than that of clinical model .The C-index of the combined model in the training cohort was higher than that of clinical model . The C-index of the combined model in the validation cohort, was higher than that of clinical model . The model combining the radiomics signature and clinical factors provided a better evaluation of PFS than the model that considered clinical factors alone.Locoregional therapies, including transarterial chemoembolization (TACE) and ablations, are proposed to postpone disease progression . TherapyA radiomics approach was applied to identify more heterogeneous information from images. Radiomics signature extracted from ultrasonic, CT and MRI images have been found to predict recurrence in HCC patients who receive surgery , liver tThe BCLC staging system and AFP level have been proven to be efficient in predicting the survival of liver cancer. Consistent with previous studies , we alsoStudies have demonstrated that TACE shows synergistic effects with RFA in improving tumour response and survival in intermediate or advanced HCC patients Z. W. . HoweverA nomogram was used to provide individual predictions; the accuracy of the predictions was verified by calculating the C-index and AUC, and they were analysed based on the calibration curve, the decision curve and the clinical impact curve . In thisAdmittedly, this study has certain limitations. As a single-centre and retrospective study, there was inevitable selection bias. Almost half of HCC patients in this study were in BCLC stage C, which have great impact on the outcome owing to the fact that the first-line treatment for these patients should be systemic therapy rather than the combination of TACE and RFA. The PFS evaluation did not comprehensively reflected the overall biological behaviours of these patients, especially who with extrahepatic metastasis. A more accurate evaluation for these patients received TACE and RFA treatment should be further investigated in future study. Besides, the sample size was relatively small, and larger datasets and external validation are urgently needed to validate our findings. In the future, large-sample, multicentre cohorts will be examined to verify the prognostic significance of these radiomics signature.This study provides a radiomics signature-based nomogram of PFS prediction for intermediate and advanced HCC patients treated with TACE and RFA. The radiomics signature was a prognostic risk factor, and the nomogram combined radiomics and clinical factors acts as a new strategy for predicting the PFS of intermediate and advanced HCC treated with TACE plus RFA. These results could be used to facilitate HCC treatment management.